Climate change and health modeling: horses for courses

Impacts of Climate Change on Health and Health Services in Northern New South Wales, Australia: A Rapid Review

Climate change is exposing populations to increasing temperatures and extreme weather events in many parts of Australia. To prepare for climate challenges, there is a growing need for Local Health Districts (LHDs) to identify potential health impacts in their region and strengthen the capacity of the health system to respond accordingly. This rapid review summarised existing evidence and research gaps on the impact of climate change on health and health services in Northern New South Wales (NSW)-a 'hotspot' for climate disaster declarations. We systematically searched online databases and selected 11 peer-reviewed studies published between 2012-2022 for the Northern NSW region. The most explored health outcome was mental health in the aftermath of floods and droughts, followed by increased healthcare utilisation due to respiratory, cardiovascular and mortality outcomes associated with bushfire smoke or heat waves. Future research directions were recommended to understand: the compounding impacts of extreme events on health and the health system, local data needs that can better inform models that predict future health risks and healthcare utilisation for the region, and the needs of vulnerable populations that require a whole-of-system response during the different phases of disasters. In conclusion, the review provided climate change and health research directions the LHD may undertake to inform future adaptation and mitigation policies and strategies relevant to their region.

Analysis of the impact of heat waves on daily mortality in urban and rural areas in Madrid

The objective of this study was to analyze and compare the effect of high temperatures on daily mortality in the urban and rural populations in Madrid. Data were analyzed from municipalities in Madrid with a population of over 10,000 inhabitants during the period from January 1, 2000 to December 31, 2020. Four groups were generated: Urban Metropolitan Center, Rural Northern Mountains, Rural Center, and Southern Rural. The dependent variable used was the rate of daily mortality due to natural causes per million inhabitants (CIE-X: A00-R99) between the months of June and September for the period. The primary independent variable was maximum daily temperature. Social and demographic "context variables" were included: population >64 years of age (%), deprivation index and housing indicators. The analysis was carried out in three phases: 1) determination of the threshold definition temperature of a heat wave (Tumbral) for each study group; 2) determination of relative risks (RR) attributable to heat for each group using Poisson linear regression (GLM), and 3) calculation of odds ratios (OR) using binomial family GLM for the frequency of the appearance of heat waves associated with context variables. The resulting percentiles (for the series of maximum daily temperatures for the summer months) corresponding to Tthreshold were: 74th percentile for Urban Metropolitan Center, 76th percentile for Southern Rural, 83rd for Rural Northern Mountains and 98th percentile for Center Rural (98). Greater vulnerability was found for the first two. In terms of context variables that explained the appearance of heat waves, deprivation index level, population >64 years of age and living in the metropolitan area were found to be risk factors. Rural and urban areas behaved differently, and socioeconomic inequality and the composition of the population over age 64 were found to best explain the vulnerability of the Rural Center and Southern Rural zones.

The impact of heat waves on daily mortality in districts in Madrid: The effect of sociodemographic factors

Although there is significant scientific evidence on the impact of heat waves, there are few studies that analyze the effects of sociodemographic factors on the impact of heat waves below the municipal level. The objective of this study was to analyze the role of income level, percent of the population over age 65, existence of air conditioning units and hectares (Ha) of green zones in districts in Madrid, in the impact of heat on daily mortality between January 1, 2010 and December 31, 2013. Seventeen districts were analyzed, and Generalized Linear (GLM) Poisson Regression Models were used to calculate relative risks (RR) and attributable risks (RA) for the impact of heat waves on mortality due to natural causes (CIEX:A00-R99). The pattern of risks obtained was analyzed using GLM univariates and multivariates of the binomial family (link logit), introducing the socioeconomic and demographic variables mentioned above. The results indicate that heat wave had an impact in only three of the districts analyzed. In the univariate models, all of the variables were statistically significant, but Ha of green zones lost significance in the multivariate model. Income level, existence of air conditioning units, and percent of the population over age 65 in the district remained as variables that modulate the impact of heat wave on daily mortality in the municipality of Madrid. Income level was the key variable that explained this behavior. The results obtained in this study show that there are factors at levels below the municipal level (district level) that should be considered as focus areas for health policy in order to decrease the impact of heat and promote the process of adaptation to heat in the context of climate change.

An Assessment of Climate Change and Health Vulnerability and Adaptation in Dominica

A climate change and health vulnerability and adaptation assessment was conducted in Dominica, a Caribbean small island developing state located in the Lesser Antilles. The assessment revealed that the country's population is already experiencing many impacts on health and health systems from climate variability and change. Infectious diseases as well as food and waterborne diseases pose continued threats as climate change may exacerbate the related health risks. Threats to food security were also identified, with particular concern for food production systems. The findings of the assessment included near-term and long-term adaptation options that can inform actions of health sector decision-makers in addressing health vulnerabilities and building resilience to climate change. Key challenges include the need for enhanced financial and human resources to build awareness of key health risks and increase adaptive capacity. Other small island developing states interested in pursuing a vulnerability and adaptation assessment may find this assessment approach, key findings, analysis, and lessons learned useful.

Temperature-related mortality impacts under and beyond Paris Agreement climate change scenarios

The Paris Agreement binds all nations to undertake ambitious efforts to combat climate change, with the commitment to Bhold warming well below 2 °C in global mean temperature (GMT), relative to pre-industrial levels, and to pursue efforts to limit warming to 1.5 °C". The 1.5 °C limit constitutes an ambitious goal for which greater evidence on its benefits for health would help guide policy and potentially increase the motivation for action. Here we contribute to this gap with an assessment on the potential health benefits, in terms of reductions in temperature-related mortality, derived from the compliance to the agreed temperature targets, compared to more extreme warming scenarios. We performed a multi-region analysis in 451 locations in 23 countries with different climate zones, and evaluated changes in heat and cold-related mortality under scenarios consistent with the Paris Agreement targets (1.5 and 2 °C) and more extreme GMT increases (3 and 4 °C), and under the assumption of no changes in demographic distribution and vulnerability. Our results suggest that limiting warming below 2 °C could prevent large increases in temperature-related mortality in most regions worldwide. The comparison between 1.5 and 2 °C is more complex and characterized by higher uncertainty, with geographical differences that indicate potential benefits limited to areas located in warmer climates, where direct climate change impacts will be more discernible.

The tale wagged by the DAG: broadening the scope of causal inference and explanation for epidemiology

'Causal inference', in 21st century epidemiology, has notably come to stand for a specific approach, one focused primarily on counterfactual and potential outcome reasoning and using particular representations, such as directed acyclic graphs (DAGs) and Bayesian causal nets. In this essay, we suggest that in epidemiology no one causal approach should drive the questions asked or delimit what counts as useful evidence. Robust causal inference instead comprises a complex narrative, created by scientists appraising, from diverse perspectives, different strands of evidence produced by myriad methods. DAGs can of course be useful, but should not alone wag the causal tale. To make our case, we first address key conceptual issues, after which we offer several concrete examples illustrating how the newly favoured methods, despite their strengths, can also: (i) limit who and what may be deemed a 'cause', thereby narrowing the scope of the field; and (ii) lead to erroneous causal inference, especially if key biological and social assumptions about parameters are poorly conceived, thereby potentially causing harm. As an alternative, we propose that the field of epidemiology consider judicious use of the broad and flexible framework of 'inference to the best explanation', an approach perhaps best developed by Peter Lipton, a philosopher of science who frequently employed epidemiologically relevant examples. This stance requires not only that we be open to being pluralists about both causation and evidence but also that we rise to the challenge of forging explanations that, in Lipton's words, aspire to 'scope, precision, mechanism, unification and simplicity'.

Addressing vulnerability, building resilience: community-based adaptation to vector-borne diseases in the context of global change

Background

The threat of a rapidly changing planet – of coupled social, environmental and climatic change – pose new conceptual and practical challenges in responding to vector-borne diseases. These include non-linear and uncertain spatial-temporal change dynamics associated with climate, animals, land, water, food, settlement, conflict, ecology and human socio-cultural, economic and political-institutional systems. To date, research efforts have been dominated by disease modeling, which has provided limited practical advice to policymakers and practitioners in developing policies and programmes on the ground.

Main body

In this paper, we provide an alternative biosocial perspective grounded in social science insights, drawing upon concepts of vulnerability, resilience, participation and community-based adaptation. Our analysis was informed by a realist review (provided in the Additional file 2) focused on seven major climate-sensitive vector-borne diseases: malaria, schistosomiasis, dengue, leishmaniasis, sleeping sickness, chagas disease, and rift valley fever. Here, we situate our analysis of existing community-based interventions within the context of global change processes and the wider social science literature. We identify and discuss best practices and conceptual principles that should guide future community-based efforts to mitigate human vulnerability to vector-borne diseases. We argue that more focused attention and investments are needed in meaningful public participation, appropriate technologies, the strengthening of health systems, sustainable development, wider institutional changes and attention to the social determinants of health, including the drivers of co-infection.

Conclusion

In order to respond effectively to uncertain future scenarios for vector-borne disease in a changing world, more attention needs to be given to building resilient and equitable systems in the present.

Electronic supplementary material

The online version of this article (doi: 10.1186/s40249-017-0375-2) contains supplementary material, which is available to authorized users.

Ancillary health effects of climate mitigation scenarios as drivers of policy uptake: a review of air quality, transportation and diet co-benefits modeling studies

Background

Significant mitigation efforts beyond the Nationally Determined Commitments (NDCs) coming out of the 2015 Paris Climate Agreement are required to avoid warming of 2°C above pre-industrial temperatures. Health co-benefits represent selected near term, positive consequences of climate policies that can offset mitigation costs in the short term before the beneficial impacts of those policies on the magnitude of climate change are evident. The diversity of approaches to modeling mitigation options and their health effects inhibits meta-analyses and syntheses of results useful in policy-making.

Methods/Design

We evaluated the range of methods and choices in modeling health co-benefits of climate mitigation to identify opportunities for increased consistency and collaboration that could better inform policy-making. We reviewed studies quantifying the health co-benefits of climate change mitigation related to air quality, transportation, and diet published since the 2009 Lancet Commission 'Managing the health effects of climate change' through January 2017. We documented approaches, methods, scenarios, health-related exposures, and health outcomes.

Results/Synthesis

Forty-two studies met the inclusion criteria. Air quality, transportation, and diet scenarios ranged from specific policy proposals to hypothetical scenarios, and from global recommendations to stakeholder-informed local guidance. Geographic and temporal scope as well as validity of scenarios determined policy relevance. More recent studies tended to use more sophisticated methods to address complexity in the relevant policy system.

Discussion

Most studies indicated significant, nearer term, local ancillary health benefits providing impetus for policy uptake and net cost savings. However, studies were more suited to describing the interaction of climate policy and health and the magnitude of potential outcomes than to providing specific accurate estimates of health co-benefits. Modeling the health co-benefits of climate policy provides policy-relevant information when the scenarios are reasonable, relevant, and thorough, and the model adequately addresses complexity. Greater consistency in selected modeling choices across the health co-benefits of climate mitigation research would facilitate evaluation of mitigation options particularly as they apply to the NDCs and promote policy uptake.

Integrating Health into Local Climate Response: Lessons from the U.S. CDC Climate-Ready States and Cities Initiative

Public health has potential to serve as a frame to convey the urgency of behavior change needed to adapt to a changing climate and reduce greenhouse gas emissions. Local governments form the backbone of climate-related public health preparedness. Yet local health agencies are often inadequately prepared and poorly integrated into climate change assessments and plans. We reviewed the climate health profiles of 16 states and two cities participating in the U.S. Centers for Disease Control and Prevention (CDC)'s Climate-Ready States and Cities Initiative (CRSCI) that aims to build local capacity to assess and respond to the health impacts of climate change. Following recommendations from a recent expert panel strategic review, we present illustrations of emerging promising practice and future directions. We found that CRSCI has strengthened climate preparedness and response in local public health agencies by identifying critical climate-health impacts and vulnerable populations, and has helped integrate health more fully into broader climate planning. Promising practice was found in all three recommendation areas identified by the expert panel (leveraging partnerships, refining assessment methodologies and enhancing communications), particularly with regard to health impacts of extreme heat. Vast needs remain, however, suggesting the need to disseminate CRSCI experience to non-grantees. In conclusion, the CRSCI program approach and selected activities illustrate a way forward toward robust, targeted local preparedness and response that may serve as a useful example for public health departments in the United States and internationally, particularly at a time of uncertain commitment to climate change agreements at the national level. https://doi.org/10.1289/EHP1838.

Global Health and Visa Policy Reform to Address Dangers of Hajj during Summer Seasons

Every year on the 12th month of the Islamic calendar, 2–3 million Muslims from over 160 countries migrate to Holy sites in Saudi Arabia to perform the Hajj, representing one of the largest mass gathering events worldwide. Yet, the Hajj poses several challenges to global health and public safety, including the unique health risks posed by seasonal variability when Hajj occurs during summer months. Specifically, pilgrims taking the journey to Mecca are at higher risk for heat illnesses, heat-related injuries and exhaustion, and stampedes, when summer temperatures can reach up to 48.7°C. In response, we propose that the Saudi government, in coordination with the Organization of Islamic Cooperation and the World Health Organization, explore the establishment of an expert committee, create and use a predictive risk modeling tool, and establish a dynamic quota on Hajj visas to limit potential heat exposure for high-risk populations when the Hajj falls on seasons associated with extreme weather exposure. As climate change is projected to lead to future increases in temperatures in the region, this form of dynamic and evidence-based policymaking is needed to ensure human health and safety for generations of Hajj pilgrims to come.

Using Uncertain Climate and Development Information in Health Adaptation Planning

To aid health adaptation decision-making, there are increasing efforts to provide climate projections at finer temporal and spatial scales. Relying solely on projected climate changes for longer-term decisions makes the implicit assumption that sources of vulnerability other than climate change will remain the same, which is not very probable. Over longer time horizons, this approach likely over estimates the extent to which climate change could alter the magnitude and pattern of health outcomes, introducing systematic bias into health management decisions. To balance this potential bias, decision-makers also need projections of other drivers of health outcomes that are, like climate change, recognized determinants of some disease burdens. Incorporating projections via an iterative process that allows for regular updates based on new knowledge and experience has the potential to improve the utility of fine-scale climate projections in health system adaptation to climate change.

Current medical research funding and frameworks are insufficient to address the health risks of global environmental change

BACKGROUND

Three major international agreements signed in 2015 are key milestones for transitioning to more sustainable and resilient societies: the UN 2030 Agenda for Sustainable Development; the Sendai Framework for Disaster Risk Reduction; and the Paris Agreement under the United Nations Framework Convention on Climate Change. Together, these agreements underscore the critical importance of understanding and managing the health risks of global changes, to ensure continued population health improvements in the face of significant social and environmental change over this century. BODY: Funding priorities of major health institutions and organizations in the U.S. and Europe do not match research investments with needs to inform implementation of these international agreements. In the U.S., the National Institutes of Health commit 0.025 % of their annual research budget to climate change and health. The European Union Seventh Framework Programme committed 0.08 % of the total budget to climate change and health; the amount committed under Horizon 2020 was 0.04 % of the budget. Two issues apparently contributing to this mismatch are viewing climate change primarily as an environmental problem, and therefore the responsibility of other research streams; and narrowly framing research into managing the health risks of climate variability and change from the perspective of medicine and traditional public health. This reductionist, top-down perspective focuses on proximate, individual level risk factors. While highly successful in reducing disease burdens, this framing is insufficient to protect health and well-being over a century that will be characterized by profound social and environmental changes.

CONCLUSIONS

International commitments in 2015 underscored the significant challenges societies will face this century from climate change and other global changes. However, the low priority placed on understanding and managing the associated health risks by national and international research institutions and organizations leaves populations poorly prepared to cope with changing health burdens. Risk-centered, systems approaches can facilitate understanding of the complex interactions and dependencies across environmental, social, and human systems. This understanding is needed to formulate effective interventions targeting socio-environmental factors that are as important for determining health burdens as are individual risk factors.

Assessment of Climate-sensitive Infectious Diseases in the Federated States of Micronesia

Background: The health impacts of climate change are an issue of growing concern in the Pacific region. Prior to 2010, no formal, structured, evidence-based approach had been used to identify the most significant health risks posed by climate change in Pacific island countries. During 2010 and 2011, the World Health Organization supported the Federated States of Micronesia (FSM) in performing a climate change and health vulnerability and adaptation assessment. This paper summarizes the priority climate-sensitive health risks in FSM, with a focus on diarrheal disease, its link with climatic variables and the implications of climate change.

Methods: The vulnerability and adaptation assessment process included a review of the literature, extensive stakeholder consultations, ranking of climate-sensitive health risks, and analysis of the available long-term data on climate and climate-sensitive infectious diseases in FSM, which involved examination of health information data from the four state hospitals in FSM between 2000 and 2010; along with each state’s rainfall, temperature and El Niño-Southern Oscillation data. Generalized linear Poisson regression models were used to demonstrate associations between monthly climate variables and cases of climate-sensitive diseases at differing temporal lags.

Results: Infectious diseases were among the highest priority climate-sensitive health risks identified in FSM, particularly diarrheal diseases, vector-borne diseases and leptospirosis. Correlation with climate data demonstrated significant associations between monthly maximum temperature and monthly outpatient cases of diarrheal disease in Pohnpei and Kosrae at a lag of one month and 0 to 3 months, respectively; no such associations were observed in Chuuk or Yap. Significant correlations between disease incidence and El Niño-Southern Oscillation cycles were demonstrated in Kosrae state.

Conclusions: Analysis of the available data demonstrated significant associations between climate variables and climate-sensitive infectious diseases. This information should prove useful in implementing health system and community adaptation strategies to avoid the most serious impacts of climate change on health in FSM.